High-throughput computational solvent screening for lignocellulosic biomass processing

König‐Mattern, Laura; Komarova, Anastasia O.; Ghosh, Arpa; Linke, Steffen; Rihko‐Struckmann, Liisa; Luterbacher, Jeremy S.; Sundmacher, Kai

doi:10.1016/j.cej.2022.139476

Cited by 8 publications

(5 citation statements)

References 97 publications

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“…Diese Techniken arbeiten mit quantenchemischen Korrelationen Struktur-Eigenschaftsbeziehungen heraus, bei der sich die Zielfunktion auf den jeweiligen Anwendungsfall anpassen lässt. [44][45][46][47] Voraussetzung für diese Techniken sind zugängliche Datensätze, im Beispiel etwa 8000 verschiedene chemische Verbindungen. Die Umfänge verschiedener Datenbanken können mehrere Größenordnungen auseinanderliegen.…”

Section: Vom Moleküldesign Zum Digitalen Zwillingunclassified

Trendbericht: Technische Chemie 2024

Bremer,

Ränger,

Friedland

2024

Nachr Chem

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Die Zirkularität von Stoffströmen, die Nachhaltigkeit, vor allem die Nutzung biogener Rohstoffe, sowie die Ressourcen‐ und Energiesicherheit sind seit Jahren wichtige Ziele. Ob in der Reaktions‐ oder der Trenntechnik, alle Bereiche der technischen Chemie profitieren von grundlegenden Stützpfeilern. Mit den darin enthaltenen methodischen Ansätzen lassen sich maßgeschneiderte Lösungen auf allen Größenskalen erstellen, Szenarien für die Energiewende entwerfen oder mit virtuellen Visualisierungen Vorstellungen von der Zukunft bekommen.

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Section: Vom Moleküldesign Zum Digitalen Zwillingunclassified

Trendbericht: Technische Chemie 2024

Bremer,

Ränger,

Friedland

2024

Nachr Chem

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“…In 2023, Konig-Mattern et al 19 used the COSMO-RS model in screening more than 8000 solvent candidates for the dissolving of lignocellulosic biomass. Also, the COSMO-RS model does not satisfy the thermodynamic consistency test for VLE data.…”

Section: Introductionmentioning

confidence: 99%

“…Developing a predictive thermodynamic model with reliable results for novel molecules, in particular for systems with no experimental data, is challenging. ,− The predictive thermodynamic models are based on the excess Gibbs free energy (G ex ) and equation of state (EoS). The most widely used predictive thermodynamic activity coefficient models, in particular for polar components, are based on the G ex .…”

Section: Introductionmentioning

confidence: 99%

“…Blumenthal et al., also, have used the COSMO-RS model to find the optimal solvent for the extraction of 5-hydroxymethylfurfural. In 2023, König-Mattern et al used the COSMO-RS model in screening more than 8000 solvent candidates for the dissolving of lignocellulosic biomass. Also, the COSMO-RS model does not satisfy the thermodynamic consistency test for VLE data .…”

Section: Introductionmentioning

confidence: 99%

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Solvent Screening for Separation of Lignin-Derived Molecules Using the NIST-UNIFAC Model

Jalalinejad

Seyf

Funke

et al. 2023

ACS Sustainable Chem. Eng.

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Liquid–liquid phase equilibria were calculated to investigate the potential separations of value-added components from products obtained by lignin depolymerization. In this study, the ability of the group-contribution model was evaluated in the prediction of mutual solubility and liquid–liquid phase equilibria of phenolic compounds. The phase equilibria behaviors of quaternary systems were evaluated by the NIST-UNIFAC model so that the predicted results were in good agreement with the available experimental data. In sequence, the partition coefficients of 29 lignin-derived molecules with complex and polar functional groups were predicted by the model with good accuracy (RMSE = 0.7424). The abilities of binary, ternary, and quaternary solvent systems were evaluated in the counter-current chromatography (CCC) separations of the products reported in the literature that are obtained through lignin depolymerization processes. Based on the empirical solvent selection criteria for CCC measurements, promising solvent systems were found for some of the lignin products. The difficult separations of some products in other cases can be attributed to the very similar chemical structures of the monomers. Finally, it was found that the NIST-UNIFAC model could qualitatively predict the solvent systems from the Arizona series, suitable for the separation of 4-hydroxybenzoic acid, vanillin, acetovanillone, syringaldehyde, acetosyringone, vanillic acid, and syringic acid.

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“…The number of experiments that can be performed is limited not only by such factors as laboratory time and financial aspects but also by the ongoing trend of restricting the usage of chemicals in the framework of green chemistry. It seems, therefore, that a screening stage, utilizing different computational methods, is necessary before starting actual experiments [46][47][48][49]. Machine learning can offer valuable help in this process.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study

Przybyłek,

Jeliński,

Mianowana

et al. 2023

Preprint

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This study explores the Edaravone solubility space encompassing both neat and binary dissolution media. The efforts were made toward revealing the concentration limits inherently associated with common pure and mixed solvents. For this purpose, the published solubility data of the title drug were scrupulously inspected and cured. This enabled to make the dataset consistent and coherent. However, the lack of some important types of solvents in the collection called for an extension of the available pool of Edaravone solubility data. Hence, new measurements were performed for collecting Edaravone solubility in polar non-protic and polar di-protic media. Such an extended set of data was used for tuning the parameters of regressors models and formulating the ensemble for predicting new data. In both phases, namely the model training and ensemble formulation, close attention was paid not only to minimizing the deviation of computed values from the experimental ones but also to ensuring the high predictive power and computing solubility for new systems. Furthermore, the environmental friendliness characteristics determined based on the common green solvent selection criteria was included in the analysis. Our applied protocol led to the conclusion that the solubility space defined by ordinary solvents is limited, and it is unlikely to find solvents that are more suited for Edaravone dissolution than those depicted in this manuscript. The theoretical framework presented in this study provides a precise guide for conducting experiments, saving time and resources in the pursuit of new findings.

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High-throughput computational solvent screening for lignocellulosic biomass processing

Cited by 8 publications

References 97 publications

Trendbericht: Technische Chemie 2024

Trendbericht: Technische Chemie 2024

Solvent Screening for Separation of Lignin-Derived Molecules Using the NIST-UNIFAC Model

Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study

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